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Lindh, M.

Publications and source records attributed to Lindh, M..

3 recordsLinked to original sources

Distinct bacterial and protist plankton diversity dynamics uncovered through DNA-based monitoring in the Baltic Sea area

Planktonic microorganisms in coastal waters form the base of food web and biogeochemical cycles. The Baltic Sea area, with its pronounced environmental gradients, serves as a model coastal environment. Yet, microbial diversity assessment across these environmental gradients has so far lacked either taxonomic scope or the integration of spatial and temporal scales. Here, we analyzed protist and bacterial diversity using DNA metabarcoding across 398 samples synchronized with national monitoring of the Baltic Sea and the Kattegat-Skagerrak. We show that salinity, unlike other environmental factors, had a stronger effect on bacterial than on protist community composition. Likewise, Bayesian modeling showed that bacterial lineages were less likely than protists to occur in both lower (<9 PSU) and higher (>15 PSU) brackish salinities. Nonetheless, protist alpha diversity increased with salinity. Changes in bacterial alpha diversity were primarily seasonal and linked to influx of deepwater taxa through vertical mixing in winter. We propose that protists are ecologically less sensitive to salinity because compartmentalization allows them to disconnect basic metabolic processes from the cell membrane. Additionally, further and more frequent dispersal of bacteria might impede local adaptation. Ultimately, DNA-based environmental monitoring expands our understanding of microbial diversity patterns and the underlying factors.

microbiology↗

Mechanisms of a sustained anti-inflammatory drug response in alveolar macrophages unraveled with mathematical modeling

Both initiation and suppression of inflammation are hallmarks of the immune response. If not balanced, the inflammation may cause extensive tissue damage, which is associated with common diseases, e.g. asthma and atherosclerosis. Anti-inflammatory drugs often come with severe side effects driven by high and fluctuating drug concentrations. To remedy this, drugs with sustained anti-inflammatory responses are desirable. However, we still lack a quantitative mechanistic understanding of such sustained effects. Here, we study the anti-inflammatory response to a common glucocorticoid drug, Dexamethasone. We find a sustained response 22 hours after drug removal. With hypothesis testing using mathematical modeling, we unravel the underlying mechanism - a slow release of Dexamethasone from the receptor-drug complex. The developed model is in agreement with time-resolved training and testing data, and is used to simulate hypothetical treatment schemes. This work opens up for a more knowledge-driven drug development, to find sustained anti-inflammatory responses and fewer side effects.

systems biology↗

Identification and capsular serotype sequetyping of Streptococcus pneumoniae strains

Correct identification of Streptococcus pneumoniae (pneumococcus) and differentiation from the closely related species of the Mitis group of the genus Streptococcus, as well as serotype identification, is important for monitoring disease epidemiology and assessing the impacts of pneumococcal vaccines. In this study, we assessed the taxonomic identifications of 422 publicly available genome sequences of S. pneumoniae, S. pseudopneumoniae and S. mitis, using different methods. Identification of S. pneumoniae, by comparative analysis of the groEL partial sequence, was possible and accurate, whereas S. pseudopneumoniae and S. mitis could be misclassified as S. pneumoniae, suggesting that groEL is unreliable as a biomarker for differentiating S. pneumoniae from its closest related species. The genome sequences of S. pneumoniae and S. pseudopneumoniae fulfilled the suggested thresholds of average nucleotide identity (ANI), i.e., > 95% genome sequence similarity to the sequence of respective type strains for identification of species, whereas none of the S. mitis genome sequences fulfilled this criterion. However, ANI analyses of all sequences versus all sequences allowed discrimination of the different species by clustering, with respect to species type strains. The in silico DNA-DNA distance method was also inconclusive for identification of S. mitis genome sequences, whereas presence of the \"Xisco\" gene proved to be a reliable biomarker for S. pneumoniae identification. Furthermore, we present an improved sequetyping protocol including two newly-designed internal sequencing primers with two PCRs, as well as an improved workflow for differentiation of serogroup 6 types. The proposed sequetyping protocol generates a more specific product by generating the whole gene PCR-product for sequencing, which increases the resolution for identification of serotypes. Validations of both protocols were performed with publicly available S. pneumoniae genome sequences, reference strains at the Culture Collection University of Gothenburg (CCUG), as well as with clinical isolates. The results were compared with serotype identifications, using real-time Q-PCR analysis, as well as the Quellung reaction or antiserum panel gel-precipitation. Our protocols provide a reliable diagnostic tool for taxonomic identification as well as serotype identification of S. pneumoniae.

microbiology↗